Over the last decade, a lot of research has been directed toward integrating performance analysis into the software development process. Traditional software development methods focus on software correctness, introducing performance issues later in the development process. This approach does not take into account the fact that performance problems may require considerable changes in design, for example, at the software architecture level, or even worse at the requirement analysis level. Several approaches were proposed in order to address early software performance analysis. Although some of them have been successfully applied, we are still far from seeing performance analysis integrated into ordinary software development. In this paper, we present a comprehensive review of recent research in the field of model-based performance prediction at software development time in order to assess the maturity of the field and point out promising research directions.

Model-based Performance Prediction in Software Development: A Survey

DI MARCO, ANTINISCA;INVERARDI, PAOLA;
2004-01-01

Abstract

Over the last decade, a lot of research has been directed toward integrating performance analysis into the software development process. Traditional software development methods focus on software correctness, introducing performance issues later in the development process. This approach does not take into account the fact that performance problems may require considerable changes in design, for example, at the software architecture level, or even worse at the requirement analysis level. Several approaches were proposed in order to address early software performance analysis. Although some of them have been successfully applied, we are still far from seeing performance analysis integrated into ordinary software development. In this paper, we present a comprehensive review of recent research in the field of model-based performance prediction at software development time in order to assess the maturity of the field and point out promising research directions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/7653
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